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ORCIDVladimir B. Berikov
Person information
- affiliation: Sobolev Institute of Mathematics, Novosibirsk, Russia
- affiliation: Novosibirsk State University, Novosibirsk, Russia
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2020 – today
- 2023
[c11]Vladimir B. Berikov
:
Ensemble Clustering with Heterogeneous Transfer Learning. AIST 2023: 255-266- [i6]A. V. Dobshik, S. K. Verbitskiy, I. A. Pestunov, K. M. Sherman, Yu. N. Sinyavskiy, A. A. Tulupov, Vladimir B. Berikov:
Acute ischemic stroke lesion segmentation in non-contrast CT images using 3D convolutional neural networks. CoRR abs/2301.06793 (2023) - 2022
- [j7]Vladimir B. Berikov:
Model and Method for Constructing a Heterogeneous Cluster Ensemble. Autom. Remote. Control. 83(12): 1944-1958 (2022) - [j6]Sergey Verbitskiy, Vladimir B. Berikov, Viacheslav Vyshegorodtsev:
ERANNs: Efficient residual audio neural networks for audio pattern recognition. Pattern Recognit. Lett. 161: 38-44 (2022) - 2021
- [c10]Vladimir B. Berikov, Alexander Litvinenko, Igor Pestunov, Yuriy Sinyavskiy:
On a Weakly Supervised Classification Problem. AIST 2021: 315-329 - [c9]Vladimir B. Berikov, Alexander Litvinenko:
Weakly Supervised Regression Using Manifold Regularization and Low-Rank Matrix Representation. MOTOR 2021: 447-461 - [i5]Vladimir B. Berikov, Alexander Litvinenko:
Solving weakly supervised regression problem using low-rank manifold regularization. CoRR abs/2104.06548 (2021) - [i4]Alexander Litvinenko, Ronald Kriemann, Vladimir B. Berikov:
Identification of unknown parameters and prediction with hierarchical matrices. CoRR abs/2104.07146 (2021) - [i3]Anna Dobshik, Andrey Tulupov, Vladimir B. Berikov:
Weakly supervised semantic segmentation of tomographic images in the diagnosis of stroke. CoRR abs/2109.01887 (2021) - 2020
- [c8]Kirill Kalmutskiy, Andrey Tulupov, Vladimir B. Berikov:
Recognition of Tomographic Images in the Diagnosis of Stroke. ICPR Workshops (5) 2020: 166-171 - [i2]Vladimir B. Berikov:
Heterogeneous Transfer Learning in Ensemble Clustering. CoRR abs/2001.07155 (2020)
2010 – 2019
- 2019
- [c7]Vladimir B. Berikov:
Semi-supervised Classification Using Multiple Clustering and Low-Rank Matrix Operations. MOTOR 2019: 529-540 - [i1]Vladimir B. Berikov, Alexander Litvinenko:
Semi-Supervised Regression using Cluster Ensemble and Low-Rank Co-Association Matrix Decomposition under Uncertainties. CoRR abs/1901.03919 (2019) - 2018
- [c6]Vladimir B. Berikov, Taisiya Vinogradova:
Regression Analysis with Cluster Ensemble and Kernel Function. AIST 2018: 211-220 - 2017
- [j5]Vladimir B. Berikov, Igor Pestunov:
Ensemble clustering based on weighted co-association matrices: Error bound and convergence properties. Pattern Recognit. 63: 427-436 (2017) - 2016
- [c5]Vladimir B. Berikov:
Cluster Ensemble with Averaged Co-Association Matrix Maximizing the Expected Margin. DOOR (Supplement) 2016: 489-500 - 2014
- [j4]Vladimir B. Berikov:
Weighted ensemble of algorithms for complex data clustering. Pattern Recognit. Lett. 38: 99-106 (2014) - 2011
- [c4]Vladimir B. Berikov:
A Latent Variable Pairwise Classification Model of a Clustering Ensemble. MCS 2011: 279-288
2000 – 2009
- 2009
- [c3]Vladimir B. Berikov:
Construction of the Ensemble of Logical Models in Cluster Analysis. ICIC (2) 2009: 581-590 - 2008
- [c2]Vladimir B. Berikov, Gennady Lbov:
Bayesian Model of Recognition on a Finite Set of Events. SETN 2008: 339-344 - 2007
- [c1]Gennady Lbov, Vladimir B. Berikov:
Construction of an Event Tree on the Basis of Expert Knowledge and Time Series. KONT/KPP 2007: 314-320 - 2003
- [j3]Vladimir B. Berikov, Alexander Litvinenko:
The influence of prior knowledge on the expected performance of a classifier. Pattern Recognit. Lett. 24(15): 2537-2548 (2003) - 2002
- [j2]Vladimir B. Berikov:
An approach to the evaluation of the performance of a discrete classifier. Pattern Recognit. Lett. 23(1-3): 227-233 (2002)
1990 – 1999
- 1999
- [j1]Vladimir B. Berikov, Igor B. Rogozin:
Regression trees for analysis of mutational spectra in nucleotide sequences. Bioinform. 15(7): 553-562 (1999)
Coauthor Index
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